Lead Software Engineer - Data Intelligence

Lead Software Engineer - Python (Data engineering), Equities Technology

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Bank's Equities Technology – Prime Services team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Design and Implement data pipelines and data stores that will be leveraged by quant models
• Work closely with Trading Desk, Production Support, Quantitative Researchers and other Global Technology teams on Data Products and Analytics
• Execute software solutions, design, develop, and technically troubleshoot with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems
• Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
• Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Add to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Advanced proficiency in Python for data engineering with exposure in capital markets, equities.
• Demonstrated ownership of data quality/observability, Lineage and Governance in production environments
• Strong knowledge of SQL and schema design for analytical and time series workloads; performance tuning on columnar data
• Expertise in data management on AWS (S3, Glue, Athena, MWAA)
• Hands-on practical experience delivering system design, application development, testing and mission critical operational data flows
• Practical cloud native experience

• Prior knowledge of Capital Markets will be a strong plus
• Data streaming knowledge on frameworks like Kafka, AMPS will be beneficial
• Familiarity and prior experience on KDB/q will be beneficial
• Experience of working with and manipulating datasets using Pandas/Numpy/Scikit will be desirable